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\begin{abstract}
In this assignment, we investigate methods to predict the presence and type of
links in a social network of $244$ supposed terrorists from a modified version
of the Profiles in Terror dataset. We develop models
based on singular value decomposition and logistic regression for two tasks. 
The first is predicting existence of links between two individuals or nodes 
and the second is predicting the type of links among the $851$ known existing links. 
Our methods use a combination of individual node properties
available as $612$ features in the dataset and also network features learned
from singular value decomposition of the adjacency matrix. We obtain an AUC of
$\opttaskoneauc{}$ for link prediction and an AUC of $\opttasktwoauc{}$ for link
type prediction task for which we also obtain a $0/1$ accuracy of $\opttasktwoacc{}$.
\end{abstract}

